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Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, par...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736363/ https://www.ncbi.nlm.nih.gov/pubmed/33318596 http://dx.doi.org/10.1038/s41598-020-78851-9 |
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author | Littleton, Evan S. Childress, Madison L. Gosting, Michaela L. Jackson, Ayana N. Kojima, Shihoko |
author_facet | Littleton, Evan S. Childress, Madison L. Gosting, Michaela L. Jackson, Ayana N. Kojima, Shihoko |
author_sort | Littleton, Evan S. |
collection | PubMed |
description | Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output. |
format | Online Article Text |
id | pubmed-7736363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77363632020-12-15 Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output Littleton, Evan S. Childress, Madison L. Gosting, Michaela L. Jackson, Ayana N. Kojima, Shihoko Sci Rep Article Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output. Nature Publishing Group UK 2020-12-14 /pmc/articles/PMC7736363/ /pubmed/33318596 http://dx.doi.org/10.1038/s41598-020-78851-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Littleton, Evan S. Childress, Madison L. Gosting, Michaela L. Jackson, Ayana N. Kojima, Shihoko Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
title | Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
title_full | Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
title_fullStr | Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
title_full_unstemmed | Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
title_short | Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
title_sort | genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736363/ https://www.ncbi.nlm.nih.gov/pubmed/33318596 http://dx.doi.org/10.1038/s41598-020-78851-9 |
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